Polymodal biological detection system

ABSTRACT

The present invention relates to a method and system for providing biological detection. The system includes: at least one polymodal sensor for collectively detecting at least two conditions; and at least one node, each node including at least one of the polymodal sensors. The system also includes at least one data collector; each data collector communicating with one or more of the at least one node, and each data collector storing local information in a local knowledge base; and at least one server, each server communicating with one or more of the at least one data collector, and each server updating a global knowledge base. The at least two conditions are utilized in detecting the presence of biological activity from either one or both knowledge bases.

FIELD OF INVENTION

The present invention is related to a distributed network of sensorsthat detect one or more conditions. More particularly, the presentinvention relates to polymodal sensors that are used to detect andreport the presence of biological activity.

BACKGROUND

Pest detection, management, and control is a multi-billion dollarindustry. Generally, property owners want to use the most economicalmeans to minimize the number of pests on the property. To this end,conventional pest detection systems typically involve two separatesteps: detection and treatment. Conventional detection involves atechnician physically inspecting premises for pests. In order todetermine if pests are present, the technician must regularly andthoroughly examine the premises. In fact, the greatest expense for mostpest control businesses is the labor associated with these regularcustomer inspections. Approximately 75 percent of the technician's timeis spent performing on-site inspections. If a technician finds pests,then the property owner may elect to enter the treatment phase.Treatment is usually fairly simple and often consists of applyingpesticide to the premises. However, after a period of time, applicationof pesticide is applied regardless of whether any pests are present ornot. And it is also known to arbitrarily pre-treat building sites withchemicals before building. In such instances, application of thepesticide is wasteful and may needlessly contribute to groundwaterpollution.

In order to reduce the labor associated with these regular customerinspections, recent advances in pest detection systems have seen avariety of sensors and systems that attempt to automatically detect thepresence of pests. For example, one known system uses a vibration sensorto detect the presence of termites in a home. When termites move nearthe vibration sensor, the sensor detects the vibration and the systemindicates that termites are present. However, this type of system isproblematic because it may be triggered by events other thantermites—for example, a person walking nearby or construction occurringin the vicinity may trigger the vibration sensor. Other known systemsalso suffer from an inability to accurately determine whether aparticular pest is present and false readings commonly occur. And thesesensors provide no adaptability for the geographical region in whichthey are located. For example, detection of pests in a tropicalenvironment may be much different in a desert environment. Thus, currentsystems are unable to detect pest activity with sufficient reliabilityto be economically feasible.

Thus, a system and method is needed that accurately determines whetherpests are present and allows property owners and/or pest managementbusinesses to minimize the number of pests on the premises by the mosteconomical means.

SUMMARY OF THE INVENTION

In light of the foregoing, it is a first aspect of the present inventionto provide a polymodal biological detection system.

Another object of the present invention is to provide a method ofdetecting biological activity, comprising: positioning one or morepolymodal sensors that detect data relating to at least two conditionsin at least one zone; accumulating the data in at least one datacollector to generate a local knowledge base; gathering information fromthe at least one data collector in at least one server; and processingthe information to generate a global knowledge base that isrepresentative of at least one biological activity in at least one zone.

Another aspect of the present invention is to provide a detectionsystem, comprising at least one polymodal sensor monitoring at least twoconditions; at least one node including the at least one polymodalsensor; at least one data collector in communication with at least onenode, each data collector maintaining a local knowledge base ofcollected sensor data from the at least one node; at least one server,each server in communication with one or more of the at least one datacollector, and each server updating a global knowledge base of collectedsensor data from the at least one data collector; and wherein the atleast two conditions are utilized in detecting the presence ofbiological activity from sensor data contained in the global knowledgebase.

Yet another goal of the present invention is to provide a detectionsystem, comprising at least one node, each node including at least twosensors for detecting at least one condition and each node generating anode signal related to at least one condition; at least one datacollector, each data collector receiving at least one node signal fromat least one node and storing local information in a local knowledgebase and each data collector generating a data collector signal relatedto the information in the local knowledge base; and at least one server,each server receiving the data collector signal from at least one datacollector and updating a global knowledge base; and wherein the at leastone server analyzes at least two conditions maintained in the globalknowledge base to determine the presence of biological activity

BRIEF DESCRIPTION OF THE DRAWING

For a complete understanding of the objects, techniques and structure ofthe invention, reference should be made to the following detaileddescription and accompanying drawing.

FIG. 1 shows a schematic view of the polymodal biological systemaccording to the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION

The present concept relates to a biological detection system thatdetects biological activity including, but is not limited to: insectactivity, rodent activity, reptilian activity, bird activity, otheranimal activity, fungal activity, mold growth, spore dissemination, orany other type of detectable biological activity.

Referring now to the drawing, it can be seen that a polymodal biologicaldetection system is generally designated by the numeral 10. Thepolymodal biological detection system 10 may include: sensors 12 forindividually or collectively detecting at least two conditions, whereintwo or more associated sensors define the polymodal nature of the sensor13; one or more nodes 14, each node 14 communicating information to oneor more data collectors 50; and each data collector 50 communicatingdata to one or more servers 100. By correlating condition informationfrom at least two conditions, the detection system 10 can accuratelydetermine whether predetermined biological activity is present.

One or more polymodal sensors 13 are grouped in particular zones tomeasure the biological activity in those respective zones. For example,a zone may be defined by the enclosed area of a home, business, or otherinhabitable or uninhabitable structure; a perimeter of a property, aregion beneath the surface of a property, or a region above a property;a region of a park; a portion of one or more trees; an area ofmarshland, swampland, or open water; or any other zone in which a usermight want to monitor biological activity.

In general, each sensor 12 may be any device that generates anelectrical or optical signal that corresponds to a characteristicassociated with biological activity. Each sensor 12 may detect at leastone condition. For example, a sensor 12 may detect any one or acombination of weight, length, width, height, volume, scent, noise,vibration, speed, chemistry, temperature, moisture, density, any otherenvironmental condition, any other measurable physical characteristic,or any other condition for detecting the presence of a particularbiology or pest. The sensor 12 may be a transducer, camera or otheroptical sensor, a series of embedded wires in an edible bait block, apressure sensing plate, a capacitive element, or any other type ofdetecting or sensing device. In other words, the sensor enables amethodology to determine the presence or quality of any one of theforegoing characteristics. It is envisioned that each sensor 12 may beconfigured to observe a characteristic trait of a pest known to frequenta particular zone. For example, a growing colony of termites is expectedto generate an expected range of detectable audible frequencies.Accordingly, the sensor can be configured to detect audible noise at theexpected range and at an expected amplitude. Or some pests are known toemit a detectable smell or odor detectable by the sensor.

Generally, at least one node 14 incorporates at least one polymodalsensor 13 to detect a biological activity condition. Each node 14 mayinclude: one polymodal sensor 13 for detecting one or more biologicalactivity conditions, one or more node processors 16 for processinginformation from the one or more polymodal sensors 13, and a nodecommunication port 20 for transmitting a node signal 21. Each node 14may transmit information to one or more data collectors 50, or transmitdata to one or more servers 100, or if desired, transmit to combinationsof data collectors 50 and servers 100.

Each node 14 will include at least two sensors 12, wherein each sensor12 may detect a different condition. For example, in a particularembodiment, a node 14 may include a polymodal sensor 13 that includes avibration sensor and a chemical sensor. This combination of a vibrationsensor and a chemical sensor could be properly deemed a polymodal sensorbecause it detects more than one condition. Although the term “polymodalsensor” includes a combination of sensors disposed in a single node 14,the term is not limited to such arrangements. For example, the term“polymodal sensor” may also include a combination of sensors disposedacross different nodes, each node having at least two sensors fordetecting one or more conditions. Moreover, each node 14 may 30 includeany number of sensors 12. For example, a node 14 may have two sensors,or any other number of sensors that can be supported by the nodeprocessor 16.

Each polymodal sensor 13 transmits a sensor signal 22 to the nodeprocessor 16. The sensor signal 22 is an electrical, optical or wirelesssignal that corresponds to a condition detected by each sensor 12.Typically, the sensor signal 22 is transmitted across a conductivematerial, such as copper wire, galvanized wire, optical fibre or thelike. The node processor 16 may receive one or more sensor signals 22from a corresponding sensor 12. Typically, each node processor 16receives one or more sensor signals 22 that originate from one or moresensors 12 located in same node 14 as the node processor 16. As used inthis specification, the term “processor” encompasses a microcontroller,a microprocessor, a digital signal processor (DSP), anapplication-specific integrated circuit (ASIC), a field programmablegate array (FPGA), a programmable logic array (PLA), or any otherdigital processing engine or device. The node processor 16 contains thenecessary hardware, software and memory for enabling the system 10. Thenode processor 16 is capable of adjusting, setting and communicating tothe sensors 12 or the polymodal sensors 13 the parameters and ranges ofparameters that are to be observed. For example, the processor mayinitially set an auditory sensor to monitor a certain range offrequencies of a predetermined amplitude for a particular kind of pest.The node processor 16 may be instructed by the server 100 to changethese parameters based upon: the season of the year; environmentalfactors, such as for example humidity and/or temperature, or for thetype of biologic activity being observed. And the processor 16 mayundertake performance tests of each sensor to ensure that they arefunctioning properly and relays this performance information to therespective data collector 50. In the alternative, the server 100 mayimplement the aforementioned changes and tests.

In any event, the node processor 16 transmits a processed signal 24between the node communication port 20. Typically, the processed signal24 is an electrical signal that travels across a bus, wire, or otherconductive material. The node communication port 20 may also be referredto as a transmitter/receiver port. Each node communication port 20 worksin tandem with each node processor 16 to transmit the node signal 21 toone or more data collectors 50 or one or more servers 100, orcombinations thereof. In various embodiments, each node communicationport 20 may directly transmit the node signal 21 to only one datacollector 50 or only one server 100. In other embodiments, each nodecommunication port 20 may directly or indirectly communicate withmultiple data collectors 50 or multiple servers 100. Although the nodesignal 21 may often represent digital data, the node signal 21 may be ananalog signal and may contain information related to the conditionssensed by the polymodal sensors 13. The node signal 21 may betransmitted wirelessly or via a hardwired medium. And as notedpreviously, information may be transmitted from the server(s) 100 and/orthe data collector(s) 50 to the nodes 14 and, if appropriate, thesensors 12 or the polymodal sensors 13.

If transmitted wirelessly, the node signal 21 may be transmitted viaradio, infrared, visible light, microwave, or any other portion orportions of the electromagnetic spectrum. If transmitted wirelessly, awireless protocol such as 802.11, Bluetooth, WEP, WAP, TDMA, CDMA, aproprietary protocol, or any other wireless protocol may be utilized totransmit the node signal 21 or other data from the node 14 to one ormore data collectors 50. The node signal 21 may also be transmitted viaa hardwire medium such as copper wire, optical fiber, or any otherhardwire medium. If transmitted in this fashion, the node signal 21 orother data may be transmitted to one or more data collectors 50 viavarious protocols including: TCP/IP, ATM, USB, FireWire, a proprietaryprotocol, or any other number of hardwired protocols. Whethertransmitted via a wireless or a hardwire medium, the data may be sent inpackets or it may be otherwise structured.

Generally, at least one data collector 50 may receive information fromone or more nodes 14, may process the information, and communicate datato one or more servers 100. Each data collector 50 may include: anode-side communication port 54 that receives one or more node signals21, the node signal including node information; one or more datacollector processors 56 for analyzing the node information; one or morememories for storing a local knowledge base 58; and a server-sidecommunication port 60 for transmitting a data collector signal 62 to theserver 100. In various embodiments, the data collector 50 may be locatedat least in part in a terrestrial server or other terrestrial computingsystem. In other embodiments, the data collector 50 may be located atleast in part in a satellite or other non-terrestrial computing system.

Typically, the data collector 50 receives one or more node signals 21,each node signal 21 corresponding to a node 14. The data collector 50may receive node signals 21 from any number of nodes 14. For example,various embodiments of the data collector 50 may receive node signals 21from any number of nodes.

The node-side communication port 54 may also be referred to as areceiver/transmitter block. If present, the node-side communication port54 may work in tandem with the data collector processor 56 to receivenode signals 21 from one or more nodes 14. The node-side communicationport 54 may convert the node signal 21 into a format signal 55.Typically, the format signal 55 is an electrical signal that travelsacross a bus, wire, or other conductive material, or the signal could bewireless.

The data collector processor(s) 56 receives the format signal 55 andtransfers some or all of the data from the sensors to the connectedlocal knowledge base via a data link 57, wherein the local knowledgebase 58 may store some operational sensor data in a usable format forlater analysis. The data collector processor 56 may store data in one ormore memories that may be located in the data collector 50. The one ormore memories may include one or a combination of RAM, SRAM, DRAM,SDRAM, flash memory, optical memory, magnetic disks, CDs, DVDs, or anyother type of memory. In any event, these memory(ies) may store thelocal knowledge base 58. The local knowledge base may comprise anaggregation of the raw node information (e.g. a table of information), acompilation of analyzed data (e.g. no raw data), or a combination of rawdata and processed data. For example, this data might be environmentalin nature such as altimeter or barometer readings. Or the data mayinclude low-level information such as recent historical settings on anyone of the associated sensors. In any event, the data collectorprocessor 56 may transmit a data collector signal 62 to the datacollector's server-side communication port 60, wherein the port 60further modifies the signal 62, which contains the original informationand modifications introduced by the processor 56 and/or the localknowledge base 58, and converts it into a port transfer signal 63. Theserver-side communication port 60 may also be referred to as atransmitter and receiver port.

The server-side communication port 60 may work in tandem with the datacollector processor 56 to transmit the port transfer signal 63 to one ormore servers 100. In various embodiments, each server-side communicationport 60 may directly transmit the port transfer signal 63 to only oneserver 100. In other embodiments, each server-side communication port 60may directly or indirectly communicate with multiple servers 100 via oneor more port transfer signals 63. Although it may represent digitaldata, port transfer signal 63 is generally an analog signal. The porttransfer signal 63 may be received wirelessly or via one or more wires.

Generally, at least one server 100 may receive data from one or moredata collectors 50 or information from one or more nodes 14, orcombinations thereof. Each server 100 may process the information, andcommunicate data to one or more servers 100 or, if required, back to thedata collectors and/or the nodes. The server(s) 100 may include a servercommunication port 102, at least one server processor 104, and one ormore server memories that store a global knowledge base 106. The server100 may also include a learning system 108 that utilizes expert systemsand/or artificial intelligence. If an expert system is employed,information received from the data collector, and in particular thelocal knowledge base may be processed. For example, the learning system108 may utilize an expert system software program to vanguard processingof data collected by the nodes 14 whereby it will validate or discountdetections by the sensors 12. In other embodiments, the learning system108 may also employ an artificial intelligence program in cooperationwith the expert system to continuously adjust threshold parameters ofthe expert system as allowed within the confines of possibilities knownby the historical data retained and continuously updated in the globalknowledge base 106 in order to improve accuracy of detections. Thelearning system 108 will then manipulate or filter the results of saidadjustments and store them in the global knowledge base 106 as furtherbasis for improvement in accuracy of such detections and to support itspredictive capability. To accomplish the aforementioned processing,adjustment, filtering and so on, the learning system 108 utilizes datalinks 109 and 111 which are connected to the server processor 104 and106, respectively.

Typically, the server 100 receives one or more port transfer signals 63,each of which corresponds to a data collector 50. Alternatively, theserver may also receive one or more node signals 21. The server 100 mayreceive port transfer signals 63 from any number of data collectors 50.For example, various embodiments of the server 100 may receive porttransfer signals 63 from one data collector, or any other number of datacollectors.

The server communication port 102 may also be referred to as a receiverand transmitter port. If present, the server communication port 102 maywork in tandem with the server processor 104 to receive port transfersignals 63 from one or more data collectors 50. The server communicationblock transforms the port transfer signal 63 into a server signal 110.And as noted, the port may transmit a transfer signal 63 back to theappropriate port 20 and/or 60. In any event, the server processor 104receives the server signal 110 and processes the information therein.The server processor 104 may store data in one or more memories that maybe located in the server 100. The one or more memories may include oneor a combination of RAM, SRAM, DRAM, SDRAM, flash memory, opticalmemory, magnetic disks, CDs, DVDs, or any other type of memory. In anyevent, these memory(ies) may store the global knowledge base 106. Theserver may include more than one server processor 104. A portion of thesoftware that runs at least in part on the one or more serverprocessors, may be referred to as a learning system 108. In other words,the learning system 108 is enabled by the server processor 104 and theglobal knowledge base 106 to detect and report biological activity asdescribed herein.

In operation, the polymodal biological detection system 10 detects atleast two conditions via one or more polymodal sensors that may bedisposed about various nodes 14. Various embodiments of the system thenutilize these at least two conditions to make an accurate determinationwhether, in fact, the sensors 12 are determining the presence of thepredetermined biological activity.

In detecting biological activity, a user may position one or morepolymodal sensors in at least one zone. A zone may be defined, forexample, by the enclosed area of a home, business, or other inhabitableor uninhabitable structure; a perimeter of a property, a region beneaththe surface of a property, or a region above a property; a region of apark; a portion of one or more trees; an area of marshland, swampland,or open water; or any other point, area, region, or volume in which auser might want to monitor biological activity. After the one or morepolymodal sensors have detected at least two conditions, one or morenode processors 16 may process the data from the sensors. The nodeprocessor 16 may also generate service interrupts, reset variousregisters of the sensors, take care of other system requirements in thenode 14, or perform numerous other tasks.

In one embodiment, the node processor 16 collects and transmits the databetween the two detected conditions in order for the data to be furtherprocessed for the determination of whether a particular biologicalactivity is present. For example, a node 14 might include a vibrationsensor to detect the presence of termites in a home. When termites movenear the vibration sensor, the sensor detects the vibration and thesystem indicates that termites are present. However, because a vibrationsensor alone might be triggered inadvertently, a node might also includea chemical sensor. By transmitting the information from the vibrationsensor and the chemical sensor, the data collector 50 may be able tomore accurately determine whether a predetermined biological activity ispresent. As mentioned previously, the polymodal detection system 10 mayemploy any combination of various sensors and is not limited to acombination of chemical and vibration sensors.

In various embodiments, each data collector 50 may include at least onedata collector processor 56. This data collector processor 56 correlatesat least two conditions in the at least one zone to aid in determiningwhether one or more nodes 14 are detecting the targeted biologicalactivity in the zone. The data processor 56 processes informationrelating to at least two conditions originating from a single node 14 ororiginating from multiple nodes. In considering the at least twoconditions, the data collector processor 56 may also considerinformation stored in the local knowledge base 58. In other embodiments,the data processor may analyze only the local knowledge base 58.

In still other embodiments, each server 100, which may include a back-upserver for redundancy, may include at least one server processor 104.The server processor 104 may correlate the at least two conditions inthe at least one zone to aid in determining whether the one or morepolymodal sensors are detecting the biological activity in the zone orin adjacent zones. The server processor 104 may process informationrelating to at least two conditions originating from a single node 14 ororiginating from multiple nodes. In correlating the at least twoconditions, the server processor 104 may also consider informationstored in the local knowledge base 58. In other embodiments, the serverprocessor 104 may analyze only the local knowledge base 58. In stillother embodiments, the server processor 104 may analyze the at least twoconditions and/or the information in the local knowledge base 58 alongwith the information in the global knowledge base 106, or combinationsthereof. Based upon the activity observed by the data collectors, andbased upon data provided by either one of or both the local and globalknowledge bases 58 and 106, the system 10 may generate reports or otherautomated alerts that are sent to an end user. These alerts may be basedon preset or predetermined threshold levels, or upon unexpectedincreases or decreases in expected biologic activity.

Thus, it can be seen that the objects of the invention have beensatisfied by the structure and its method for use presented above. Whilein accordance with the Patent Statutes, only the best mode and preferredembodiment has been presented and described in detail, it is to beunderstood that the invention is not limited thereto and thereby.Accordingly, for an appreciation of the true scope and breadth of theinvention, reference should be made to the following claims.

1. A method of detecting biological activity, comprising: positioningone or more polymodal sensors that detect data relating to at least twoconditions in at least one zone; accumulating the data in at least onedata collector to generate a local knowledge base; gathering informationfrom the at least one data collector in at least one server; andprocessing the information to generate a global knowledge base that isrepresentative of at least one biological activity in at least one zone.2. The method of claim 1, further comprising: positioning at least twopolymodal sensors in each zone; and detecting data by each saidpolymodal sensor relating to at least two conditions.
 3. The method ofclaim 1, further comprising: associating the one or more polymodalsensors with a node processor that transmit the at least two conditionsto aid in determining whether the polymodal sensors are detecting the atleast one biological activity in the at least one zone.
 4. The method ofclaim 1, further comprising: correlating the at least two conditions inthe at least one zone to aid in determining whether the one or morepolymodal sensors are detecting the biological activity in the zone. 5.The method of claim 1, further comprising: correlating the at least twoconditions in the at least one zone to determine whether the polymodalsensors are detecting the biological activity in the at least one zone.6. The method of claim 1, further comprising: alerting an end user as towhether to treat insects, pests, or other biological activity based uponthe local knowledge base and predetermined threshold levels.
 7. Themethod of claim 1, further comprising: alerting an end user as towhether to treat insects, pests, or other biological activity based uponthe global knowledge base and predetermined threshold levels.
 8. Adetection system, comprising: at least one polymodal sensor monitoringat least two conditions; at least one node including the at least onepolymodal sensor; at least one data collector in communication with atleast one node, each data collector maintaining a local knowledge baseof collected sensor data from the at least one node; at least oneserver, each server in communication with one or more of the at leastone data collector, and each server updating a global knowledge base ofcollected sensor data from the at least one data collector; and whereinthe at least two conditions are utilized in detecting the presence ofbiological activity from sensor data contained in the global knowledgebase.
 9. The detection system of claim 8, further comprising: aprocessor contained in each node that processes data relating to the oneor more sensors of the node.
 10. The detection system of claim 9,further comprising: a node communication port contained in each nodethat communicates with the data collector.
 11. The detection system ofclaim 10, wherein the communication block communicates with the datacollector via a wireless or wired signal.
 12. The detection system ofclaim 11, wherein at least one data collector is located at least inpart in one of a satellite and non-terrestrial monitoring system. 13.The detection system of claim 8 wherein the data collector comprises: anode-side communication port that communicates with one or more of theat least one node; a data collector processor that processes informationrelated to the at least two conditions; and a server-side communicationport that communicates with one or more of the at least one server. 14.The detection system of claim 13, wherein the local knowledge base ismaintained within said data collector processor.
 15. The detectionsystem of claim 8 wherein the server includes: a server communicationport that communicates with one or more of the at least one datacollectors; a server processor that processes information related to theat least two conditions received from the server communication port; anda learning system connected to the server processor that utilizes atleast an expert system to analyze the at least two conditions indetecting the presence of biological activity.
 16. The detection systemof claim 15, wherein the global knowledge base is linked to the learningsystem.
 17. The detection system of claim 8, wherein each data collectorstores information related to biological activity in the local knowledgebase.
 18. The detection system of claim 8, wherein each server storesinformation related to biological activity in the global knowledge base.19. A detection system, comprising: at least one node, each nodeincluding at least two sensors for detecting at least one condition andeach node generating a node signal related to at least one condition; atleast one data collector, each data collector receiving at least onenode signal from at least one node and storing local information in alocal knowledge base and each data collector generating a data collectorsignal related to the information in the local knowledge base; and atleast one server, each server receiving the data collector signal fromat least one data collector and updating a global knowledge base; andwherein the at least one server analyzes at least two conditionsmaintained in the global knowledge base to determine the presence ofbiological activity.